Design of Artificial Neural Networks for Fuzzy Control System


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 2, No. 5, pp. 626-633, Sep. 1995
10.3745/KIPSTE.1995.2.5.626,   PDF Download:

Abstract

It is very hard to identify the fuzzy rules and tune the membership functions of the fuzzy inference in fuzzy systems modeling. We propose a fuzzy neural network model which can automatically identify the fuzzy rules and tune the membership functions of fuzzy inference simultaneously using artificial neural networks, and modify backpropagation algorithm for improving the convergence. The proposed method is verified by the simulation for a robot manipulator.


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Cite this article
[IEEE Style]
J. M. Suk and C. D. Chul, "Design of Artificial Neural Networks for Fuzzy Control System," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 2, no. 5, pp. 626-633, 1995. DOI: 10.3745/KIPSTE.1995.2.5.626.

[ACM Style]
Jang Moon Suk and Chang Duk Chul. 1995. Design of Artificial Neural Networks for Fuzzy Control System. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 2, 5, (1995), 626-633. DOI: 10.3745/KIPSTE.1995.2.5.626.